Overview

Dataset statistics

Number of variables18
Number of observations777
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory109.4 KiB
Average record size in memory144.2 B

Variable types

NUM17
CAT1

Warnings

Accept is highly correlated with Apps and 1 other fieldsHigh correlation
Apps is highly correlated with AcceptHigh correlation
Enroll is highly correlated with Accept and 1 other fieldsHigh correlation
F.Undergrad is highly correlated with EnrollHigh correlation
Names has unique values Unique

Reproduction

Analysis started2020-10-09 13:29:17.021507
Analysis finished2020-10-09 13:30:23.629815
Duration1 minute and 6.61 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Names
Categorical

UNIQUE

Distinct777
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
Pacific University
 
1
Centenary College of Louisiana
 
1
Austin College
 
1
SUNY College at Cortland
 
1
Marist College
 
1
Other values (772)
772 
ValueCountFrequency (%) 
Pacific University10.1%
 
Centenary College of Louisiana10.1%
 
Austin College10.1%
 
SUNY College at Cortland10.1%
 
Marist College10.1%
 
Colorado College10.1%
 
Carroll College10.1%
 
Florida International University10.1%
 
Oklahoma State University10.1%
 
Campbell University10.1%
 
Other values (767)76798.7%
 
2020-10-09T19:00:23.799360image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique777 ?
Unique (%)100.0%
2020-10-09T19:00:23.997829image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length45
Median length21
Mean length22.17631918
Min length11

Apps
Real number (ℝ≥0)

HIGH CORRELATION

Distinct711
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3001.638353
Minimum81
Maximum48094
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:24.168378image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum81
5-th percentile329.8
Q1776
median1558
Q33624
95-th percentile11066.2
Maximum48094
Range48013
Interquartile range (IQR)2848

Descriptive statistics

Standard deviation3870.201484
Coefficient of variation (CV)1.289363018
Kurtosis26.77425316
Mean3001.638353
Median Absolute Deviation (MAD)987
Skewness3.723749968
Sum2332273
Variance14978459.53
MonotocityNot monotonic
2020-10-09T19:00:24.332935image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
66330.4%
 
44030.4%
 
100630.4%
 
124320.3%
 
180020.3%
 
58420.3%
 
92020.3%
 
143220.3%
 
80920.3%
 
477220.3%
 
Other values (701)75497.0%
 
ValueCountFrequency (%) 
8110.1%
 
10010.1%
 
14110.1%
 
15010.1%
 
15210.1%
 
ValueCountFrequency (%) 
4809410.1%
 
2180410.1%
 
2019210.1%
 
1987310.1%
 
1931510.1%
 

Accept
Real number (ℝ≥0)

HIGH CORRELATION

Distinct693
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.804376
Minimum72
Maximum26330
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:24.492539image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum72
5-th percentile272.4
Q1604
median1110
Q32424
95-th percentile6979.2
Maximum26330
Range26258
Interquartile range (IQR)1820

Descriptive statistics

Standard deviation2451.113971
Coefficient of variation (CV)1.2141414
Kurtosis18.93809941
Mean2018.804376
Median Absolute Deviation (MAD)680
Skewness3.417727343
Sum1568611
Variance6007959.699
MonotocityNot monotonic
2020-10-09T19:00:24.659065image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
45240.5%
 
38430.4%
 
49430.4%
 
34030.4%
 
56230.4%
 
50130.4%
 
55830.4%
 
88830.4%
 
40530.4%
 
172520.3%
 
Other values (683)74796.1%
 
ValueCountFrequency (%) 
7210.1%
 
9010.1%
 
11810.1%
 
12810.1%
 
13020.3%
 
ValueCountFrequency (%) 
2633010.1%
 
1874410.1%
 
1509610.1%
 
1324310.1%
 
1300710.1%
 

Enroll
Real number (ℝ≥0)

HIGH CORRELATION

Distinct581
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean779.972973
Minimum35
Maximum6392
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:24.938317image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile118.6
Q1242
median434
Q3902
95-th percentile2757
Maximum6392
Range6357
Interquartile range (IQR)660

Descriptive statistics

Standard deviation929.1761901
Coefficient of variation (CV)1.191292804
Kurtosis8.831543926
Mean779.972973
Median Absolute Deviation (MAD)239
Skewness2.690464654
Sum606039
Variance863368.3923
MonotocityNot monotonic
2020-10-09T19:00:25.188645image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
29550.6%
 
17750.6%
 
45840.5%
 
17240.5%
 
17640.5%
 
36640.5%
 
45240.5%
 
47840.5%
 
28440.5%
 
22740.5%
 
Other values (571)73594.6%
 
ValueCountFrequency (%) 
3510.1%
 
4610.1%
 
5110.1%
 
5520.3%
 
6310.1%
 
ValueCountFrequency (%) 
639210.1%
 
618010.1%
 
587410.1%
 
587310.1%
 
570510.1%
 

Top10perc
Real number (ℝ≥0)

Distinct82
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.55855856
Minimum1
Maximum96
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:25.422057image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q115
median23
Q335
95-th percentile65.2
Maximum96
Range95
Interquartile range (IQR)20

Descriptive statistics

Standard deviation17.64036439
Coefficient of variation (CV)0.6401047554
Kurtosis2.208064686
Mean27.55855856
Median Absolute Deviation (MAD)9
Skewness1.413216781
Sum21413
Variance311.1824557
MonotocityNot monotonic
2020-10-09T19:00:25.584591image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20374.8%
 
10354.5%
 
12324.1%
 
16314.0%
 
15283.6%
 
25283.6%
 
23263.3%
 
19222.8%
 
14222.8%
 
22212.7%
 
Other values (72)49563.7%
 
ValueCountFrequency (%) 
130.4%
 
220.3%
 
360.8%
 
420.3%
 
5111.4%
 
ValueCountFrequency (%) 
9610.1%
 
9530.4%
 
9030.4%
 
8910.1%
 
8720.3%
 

Top25perc
Real number (ℝ≥0)

Distinct89
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.7966538
Minimum9
Maximum100
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:25.744193image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile25.8
Q141
median54
Q369
95-th percentile93
Maximum100
Range91
Interquartile range (IQR)28

Descriptive statistics

Standard deviation19.8047776
Coefficient of variation (CV)0.354945615
Kurtosis-0.5641208067
Mean55.7966538
Median Absolute Deviation (MAD)14
Skewness0.2593403527
Sum43354
Variance392.2292156
MonotocityNot monotonic
2020-10-09T19:00:25.905764image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
55202.6%
 
60202.6%
 
50192.4%
 
36192.4%
 
52182.3%
 
40172.2%
 
53172.2%
 
57172.2%
 
63162.1%
 
47162.1%
 
Other values (79)59877.0%
 
ValueCountFrequency (%) 
910.1%
 
1210.1%
 
1320.3%
 
1410.1%
 
1610.1%
 
ValueCountFrequency (%) 
10070.9%
 
9950.6%
 
9830.4%
 
9710.1%
 
9670.9%
 

F.Undergrad
Real number (ℝ≥0)

HIGH CORRELATION

Distinct714
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3699.907336
Minimum139
Maximum31643
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:26.073316image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum139
5-th percentile509.8
Q1992
median1707
Q34005
95-th percentile14477.8
Maximum31643
Range31504
Interquartile range (IQR)3013

Descriptive statistics

Standard deviation4850.420531
Coefficient of variation (CV)1.3109573
Kurtosis7.696586379
Mean3699.907336
Median Absolute Deviation (MAD)972
Skewness2.610457948
Sum2874828
Variance23526579.33
MonotocityNot monotonic
2020-10-09T19:00:26.236875image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
134530.4%
 
130630.4%
 
111530.4%
 
66230.4%
 
50030.4%
 
95930.4%
 
170730.4%
 
61420.3%
 
41620.3%
 
69020.3%
 
Other values (704)75096.5%
 
ValueCountFrequency (%) 
13910.1%
 
19910.1%
 
20110.1%
 
24910.1%
 
28220.3%
 
ValueCountFrequency (%) 
3164310.1%
 
3001710.1%
 
2893810.1%
 
2737810.1%
 
2664010.1%
 

P.Undergrad
Real number (ℝ≥0)

Distinct566
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean855.2985843
Minimum1
Maximum21836
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:26.407420image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20
Q195
median353
Q3967
95-th percentile3303.6
Maximum21836
Range21835
Interquartile range (IQR)872

Descriptive statistics

Standard deviation1522.431887
Coefficient of variation (CV)1.780000476
Kurtosis55.03451787
Mean855.2985843
Median Absolute Deviation (MAD)303
Skewness5.692353167
Sum664567
Variance2317798.851
MonotocityNot monotonic
2020-10-09T19:00:26.565004image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3070.9%
 
16660.8%
 
3550.6%
 
140.5%
 
9540.5%
 
4440.5%
 
4540.5%
 
5340.5%
 
2840.5%
 
2740.5%
 
Other values (556)73194.1%
 
ValueCountFrequency (%) 
140.5%
 
210.1%
 
320.3%
 
410.1%
 
540.5%
 
ValueCountFrequency (%) 
2183610.1%
 
1096210.1%
 
1022110.1%
 
931010.1%
 
905410.1%
 

Outstate
Real number (ℝ≥0)

Distinct640
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10440.66924
Minimum2340
Maximum21700
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:26.722546image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2340
5-th percentile4601.6
Q17320
median9990
Q312925
95-th percentile18498
Maximum21700
Range19360
Interquartile range (IQR)5605

Descriptive statistics

Standard deviation4023.016484
Coefficient of variation (CV)0.385321706
Kurtosis-0.4138324002
Mean10440.66924
Median Absolute Deviation (MAD)2780
Skewness0.5092779742
Sum8112400
Variance16184661.63
MonotocityNot monotonic
2020-10-09T19:00:26.895084image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
6550131.7%
 
840050.6%
 
1050050.6%
 
884050.6%
 
990040.5%
 
513040.5%
 
1120040.5%
 
784440.5%
 
780040.5%
 
1080040.5%
 
Other values (630)72593.3%
 
ValueCountFrequency (%) 
234010.1%
 
258010.1%
 
270010.1%
 
304010.1%
 
346010.1%
 
ValueCountFrequency (%) 
2170010.1%
 
2010010.1%
 
1996410.1%
 
1996010.1%
 
1990010.1%
 

Room.Board
Real number (ℝ≥0)

Distinct553
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4357.526384
Minimum1780
Maximum8124
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:27.069650image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1780
5-th percentile2735.8
Q13597
median4200
Q35050
95-th percentile6382
Maximum8124
Range6344
Interquartile range (IQR)1453

Descriptive statistics

Standard deviation1096.696416
Coefficient of variation (CV)0.2516786633
Kurtosis-0.187552717
Mean4357.526384
Median Absolute Deviation (MAD)678
Skewness0.4773555795
Sum3385798
Variance1202743.028
MonotocityNot monotonic
2020-10-09T19:00:27.261137image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
410091.2%
 
370070.9%
 
360070.9%
 
420060.8%
 
340060.8%
 
375060.8%
 
450050.6%
 
460050.6%
 
444050.6%
 
400050.6%
 
Other values (543)71692.1%
 
ValueCountFrequency (%) 
178010.1%
 
188010.1%
 
192010.1%
 
214610.1%
 
219010.1%
 
ValueCountFrequency (%) 
812410.1%
 
742510.1%
 
740010.1%
 
739810.1%
 
735010.1%
 

Books
Real number (ℝ≥0)

Distinct122
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean549.3809524
Minimum96
Maximum2340
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:27.431651image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum96
5-th percentile350
Q1470
median500
Q3600
95-th percentile765.6
Maximum2340
Range2244
Interquartile range (IQR)130

Descriptive statistics

Standard deviation165.1053601
Coefficient of variation (CV)0.3005298226
Kurtosis28.33309728
Mean549.3809524
Median Absolute Deviation (MAD)100
Skewness3.485024736
Sum426869
Variance27259.77995
MonotocityNot monotonic
2020-10-09T19:00:27.589228image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
50017822.9%
 
60012816.5%
 
400769.8%
 
450607.7%
 
550415.3%
 
700283.6%
 
650182.3%
 
630172.2%
 
300141.8%
 
350141.8%
 
Other values (112)20326.1%
 
ValueCountFrequency (%) 
9610.1%
 
11010.1%
 
12010.1%
 
20020.3%
 
22110.1%
 
ValueCountFrequency (%) 
234010.1%
 
200010.1%
 
149510.1%
 
140010.1%
 
130010.1%
 

Personal
Real number (ℝ≥0)

Distinct294
Distinct (%)37.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1340.642214
Minimum250
Maximum6800
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:27.749798image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile500
Q1850
median1200
Q31700
95-th percentile2488.8
Maximum6800
Range6550
Interquartile range (IQR)850

Descriptive statistics

Standard deviation677.0714536
Coefficient of variation (CV)0.505035159
Kurtosis7.124017051
Mean1340.642214
Median Absolute Deviation (MAD)400
Skewness1.742496537
Sum1041679
Variance458425.7533
MonotocityNot monotonic
2020-10-09T19:00:27.906381image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1000455.8%
 
1200334.2%
 
1500324.1%
 
800324.1%
 
900273.5%
 
500263.3%
 
600233.0%
 
1100233.0%
 
750172.2%
 
700162.1%
 
Other values (284)50364.7%
 
ValueCountFrequency (%) 
25010.1%
 
30040.5%
 
35010.1%
 
40070.9%
 
42010.1%
 
ValueCountFrequency (%) 
680010.1%
 
491310.1%
 
428810.1%
 
420010.1%
 
411010.1%
 

PhD
Real number (ℝ≥0)

Distinct78
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.66023166
Minimum8
Maximum103
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:28.070976image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile43.8
Q162
median75
Q385
95-th percentile95
Maximum103
Range95
Interquartile range (IQR)23

Descriptive statistics

Standard deviation16.32815469
Coefficient of variation (CV)0.2247192765
Kurtosis0.564772824
Mean72.66023166
Median Absolute Deviation (MAD)12
Skewness-0.768170112
Sum56457
Variance266.6086355
MonotocityNot monotonic
2020-10-09T19:00:28.228520image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
77263.3%
 
73243.1%
 
90233.0%
 
81212.7%
 
82212.7%
 
71212.7%
 
75212.7%
 
76202.6%
 
89202.6%
 
79192.4%
 
Other values (68)56172.2%
 
ValueCountFrequency (%) 
810.1%
 
1020.3%
 
1410.1%
 
1610.1%
 
2210.1%
 
ValueCountFrequency (%) 
10310.1%
 
10030.4%
 
9960.8%
 
9820.3%
 
9770.9%
 

Terminal
Real number (ℝ≥0)

Distinct65
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.7027027
Minimum24
Maximum100
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:28.385103image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile52.8
Q171
median82
Q392
95-th percentile98
Maximum100
Range76
Interquartile range (IQR)21

Descriptive statistics

Standard deviation14.72235853
Coefficient of variation (CV)0.1847159259
Kurtosis0.2420189636
Mean79.7027027
Median Absolute Deviation (MAD)10
Skewness-0.8165423363
Sum61929
Variance216.7478406
MonotocityNot monotonic
2020-10-09T19:00:28.546668image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
96303.9%
 
92293.7%
 
90283.6%
 
95263.3%
 
89263.3%
 
75253.2%
 
93253.2%
 
98233.0%
 
97233.0%
 
88222.8%
 
Other values (55)52066.9%
 
ValueCountFrequency (%) 
2410.1%
 
2510.1%
 
3010.1%
 
3320.3%
 
3510.1%
 
ValueCountFrequency (%) 
100141.8%
 
99131.7%
 
98233.0%
 
97233.0%
 
96303.9%
 

S.F.Ratio
Real number (ℝ≥0)

Distinct173
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.08970399
Minimum2.5
Maximum39.8
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:28.713258image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum2.5
5-th percentile8.3
Q111.5
median13.6
Q316.5
95-th percentile21
Maximum39.8
Range37.3
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.958349135
Coefficient of variation (CV)0.2809391268
Kurtosis2.561208675
Mean14.08970399
Median Absolute Deviation (MAD)2.3
Skewness0.6674353642
Sum10947.7
Variance15.66852788
MonotocityNot monotonic
2020-10-09T19:00:28.876786image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
12.1151.9%
 
11.3141.8%
 
12.5131.7%
 
13.3131.7%
 
11.1131.7%
 
11.5121.5%
 
12.8121.5%
 
12.7111.4%
 
15.1111.4%
 
13111.4%
 
Other values (163)65283.9%
 
ValueCountFrequency (%) 
2.510.1%
 
2.910.1%
 
3.310.1%
 
3.910.1%
 
4.310.1%
 
ValueCountFrequency (%) 
39.810.1%
 
28.810.1%
 
27.810.1%
 
27.610.1%
 
27.210.1%
 

perc.alumni
Real number (ℝ≥0)

Distinct61
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.74388674
Minimum0
Maximum64
Zeros2
Zeros (%)0.3%
Memory size6.1 KiB
2020-10-09T19:00:29.045336image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q113
median21
Q331
95-th percentile46
Maximum64
Range64
Interquartile range (IQR)18

Descriptive statistics

Standard deviation12.39180149
Coefficient of variation (CV)0.5448409777
Kurtosis-0.09680657195
Mean22.74388674
Median Absolute Deviation (MAD)9
Skewness0.6068912184
Sum17672
Variance153.5567442
MonotocityNot monotonic
2020-10-09T19:00:29.678674image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
10324.1%
 
16314.0%
 
17273.5%
 
26273.5%
 
24263.3%
 
9253.2%
 
13253.2%
 
15253.2%
 
20253.2%
 
8253.2%
 
Other values (51)50965.5%
 
ValueCountFrequency (%) 
020.3%
 
120.3%
 
230.4%
 
350.6%
 
4162.1%
 
ValueCountFrequency (%) 
6410.1%
 
6310.1%
 
6030.4%
 
5810.1%
 
5710.1%
 

Expend
Real number (ℝ≥0)

Distinct744
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9660.171171
Minimum3186
Maximum56233
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:29.845196image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum3186
5-th percentile4795.8
Q16751
median8377
Q310830
95-th percentile17974.8
Maximum56233
Range53047
Interquartile range (IQR)4079

Descriptive statistics

Standard deviation5221.76844
Coefficient of variation (CV)0.5405461609
Kurtosis18.77149968
Mean9660.171171
Median Absolute Deviation (MAD)1842
Skewness3.459321715
Sum7505953
Variance27266865.64
MonotocityNot monotonic
2020-10-09T19:00:30.012780image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
704120.3%
 
794020.3%
 
593520.3%
 
490020.3%
 
1087220.3%
 
711420.3%
 
884720.3%
 
697120.3%
 
832420.3%
 
689820.3%
 
Other values (734)75797.4%
 
ValueCountFrequency (%) 
318610.1%
 
336510.1%
 
348010.1%
 
360510.1%
 
373310.1%
 
ValueCountFrequency (%) 
5623310.1%
 
4570210.1%
 
4292610.1%
 
4176610.1%
 
4038610.1%
 

Grad.Rate
Real number (ℝ≥0)

Distinct81
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.46332046
Minimum10
Maximum118
Zeros0
Zeros (%)0.0%
Memory size6.1 KiB
2020-10-09T19:00:30.171362image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile37
Q153
median65
Q378
95-th percentile94.2
Maximum118
Range108
Interquartile range (IQR)25

Descriptive statistics

Standard deviation17.1777099
Coefficient of variation (CV)0.2624020562
Kurtosis-0.2052264909
Mean65.46332046
Median Absolute Deviation (MAD)12
Skewness-0.1137772909
Sum50865
Variance295.0737173
MonotocityNot monotonic
2020-10-09T19:00:30.339873image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
72243.1%
 
67233.0%
 
58222.8%
 
63222.8%
 
65212.7%
 
64202.6%
 
83202.6%
 
52202.6%
 
68182.3%
 
53172.2%
 
Other values (71)57073.4%
 
ValueCountFrequency (%) 
1010.1%
 
1520.3%
 
1810.1%
 
2130.4%
 
2210.1%
 
ValueCountFrequency (%) 
11810.1%
 
100101.3%
 
9950.6%
 
9850.6%
 
9750.6%
 

Interactions

2020-10-09T18:59:37.993175image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:38.235642image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:38.379289image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:38.520880image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:38.660539image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:38.796175image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:38.939791image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:39.076394image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:39.227025image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:39.368645image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:39.504249image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:39.645869image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:39.780509image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:39.935098image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:40.306141image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:40.451729image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:40.590380image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:40.731965image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:40.875581image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:41.018200image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:41.157868image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:41.297487image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:41.432095image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:41.580731image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:41.720328image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:41.869927image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:42.015534image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:42.151204image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:42.296815image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:42.434413image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:42.582020image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:42.724672image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:42.868292image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:43.002898image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:43.145546image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:43.286137image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:43.431749image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:43.582346image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:43.738958image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:43.904484image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:44.077023image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:44.225658image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:44.378251image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:44.528848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:44.670438image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:44.843973image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:45.025519image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:45.178080image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:45.331669image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:45.479307image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:45.623887image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:45.776511image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:45.912152image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:46.051744image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:46.191370image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:46.330995image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:46.466633image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:46.611279image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:46.747881image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:46.899477image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:47.048080image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:47.182720image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:47.330324image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:47.469962image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:47.613566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:47.765163image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:47.908810image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:48.043451image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:48.179089image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:48.311734image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:48.451363image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:48.590988image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:48.727588image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:48.864256image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:49.007872image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:49.143478image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:49.290118image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:49.701023image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:49.843637image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:49.988218image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:50.119869image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:50.262484image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:50.403112image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:50.555702image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:50.698320image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:50.832961image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:50.979567image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:51.134186image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:51.280761image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:51.428387image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:51.574010image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:51.728597image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:51.871216image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:52.029759image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:52.183388image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:52.323008image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:52.474572image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:52.617234image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:52.768785image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:52.921407image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:53.067983image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:53.212629image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:53.355216image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:53.492846image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:53.634505image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:53.779114image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:53.913722image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:54.044373image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:54.183999image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:54.320668image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:54.467242image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:54.607898image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:54.741511image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:54.888149image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:55.016772image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:55.154405image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:55.296059image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:55.432700image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:55.567335image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:55.701945image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:55.862544image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:56.017098image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:56.175676image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:56.337243image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:56.486845image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:56.656391image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:56.810976image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:56.980555image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:57.138787image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:57.293375image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:57.460961image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:57.611556image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:57.777085image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:57.940681image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:58.101214image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:58.257797image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:58.544030image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:58.694631image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:58.885118image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:59.046696image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:59.231225image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:59.382789image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:59.541365image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:59.688005image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T18:59:59.852535image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:00.005125image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:00.158713image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:00.314332image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:00.457947image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:00.615492image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:00.776062image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:00.922703image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:01.065299image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:01.543048image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:01.681643image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:01.818277image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:01.964916image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:02.104513image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:02.242174image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:02.383799image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:02.520433image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:02.667045image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:02.814647image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:02.945297image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:03.084890image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:03.220529image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:03.360189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:03.503770image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:03.637414image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:03.774049image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:03.911679image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:04.065300image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:04.217861image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:04.379461image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:04.531025image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:04.682618image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:04.878094image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:05.033711image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:05.197276image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:05.357812image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:05.510404image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:05.671972image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:05.823567image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:05.989125image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:06.145737image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:06.303285image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:06.456876image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:06.683268image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:06.830918image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:06.972495image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:07.112635image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:07.244319image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:07.429790image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:07.571443image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:07.705054image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:07.853691image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:07.994313image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:08.121941image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:08.263593image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:08.403189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:08.555779image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:08.696404image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:08.835033image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:08.971702image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:09.108335image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:09.257935image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:09.410494image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:09.560127image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:09.715679image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:09.862321image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:10.014879image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:10.161518image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:10.323090image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:10.481667image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:10.627246image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:10.786816image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:10.929436image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:11.079066image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:11.238640image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:11.393195image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:11.544820image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:11.695387image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:11.849973image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:11.997577image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:12.144187image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:12.297775image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:12.442390image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:12.597011image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:12.749566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:12.911170image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:13.066721image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:13.210334image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:13.367914image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:13.513526image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:13.666117image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:13.826719image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:13.978314image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:14.120938image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:14.266554image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:14.414117image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:14.560756image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:14.705337image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:14.848953image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:14.990611image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:15.140207image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:15.284791image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:15.440405image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:15.972982image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:16.116566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:16.270157image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:16.409812image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:16.560378image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:16.710979image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:16.854625image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.001200image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.141823image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.275498image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.416089image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.560704image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.696340image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.834973image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:17.971640image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:18.112263image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:18.258871image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:18.398501image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:18.549097image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:18.693706image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:18.827351image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:18.966944image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:19.108566image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:19.247195image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:19.382832image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:19.519502image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:19.662118image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:19.804704image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:19.944362image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:20.083000image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:20.227574image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:20.372218image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:20.510816image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:20.670422image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:20.829964image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:21.034416image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:21.193990image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:21.370517image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:21.544055image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:21.742525image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:21.934011image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:22.122506image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-10-09T19:00:30.502473image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-10-09T19:00:30.913481image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-10-09T19:00:31.208658image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-10-09T19:00:31.533789image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-10-09T19:00:22.835937image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-10-09T19:00:23.344577image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

NamesAppsAcceptEnrollTop10percTop25percF.UndergradP.UndergradOutstateRoom.BoardBooksPersonalPhDTerminalS.F.Ratioperc.alumniExpendGrad.Rate
0Abilene Christian University1660123272123522885537744033004502200707818.112704160
1Adelphi University218619245121629268312271228064507501500293012.2161052756
2Adrian College1428109733622501036991125037504001165536612.930873554
3Agnes Scott College41734913760895106312960545045087592977.7371901659
4Alaska Pacific University193146551644249869756041208001500767211.921092215
5Albertson College58747915838626784113500333550067567739.411972755
6Albertus Magnus College35334010317454162301329057205001500909311.526886163
7Albion College1899172048937681594321386848264508508910013.7371148773
8Albright College10388392273063973306155954400300500798411.3231164480
9Alderson-Broaddus College5824981722144799781046833806601800404111.515899152

Last rows

NamesAppsAcceptEnrollTop10percTop25percF.UndergradP.UndergradOutstateRoom.BoardBooksPersonalPhDTerminalS.F.Ratioperc.alumniExpendGrad.Rate
767Winthrop University2320180576924613395670640033925802150718012.826672959
768Wisconsin Lutheran College1521287517412822291003700500140048488.526896050
769Wittenberg University1979173957542681980144159484404400800829512.8291041478
770Wofford College150193527351831059341268041506051440919215.342787575
771Worcester Polytechnic Institute276823146824986280286158845370530730929415.2341077482
772Worcester State College2197151554342630892029679739005001200606021.014446940
773Xavier University195918056952447284911071152049606001250737513.331918983
774Xavier University of Louisiana209719156953461279316669004200617781677514.420832349
775Yale University10705245313179599521783198406510630211596965.8494038699
776York College of Pennsylvania29891855691286329881726499035605001250757518.128450999